Keywords: Internet of Meaning, HESTIA, Domain-Specific Modeling
Astract: At first glance, the Internet of Things brings about an expectation for users (be it individuals or organizations) to interact with the many Internet-connected “things” in a natural way while also enhancing everyday work and life. The emergence of smart cities, and smart homes, also fuels the need for a broad audience to interact with the Internet of Things in a natural way. In current practice, however, users are confronted with the need to negotiate a complex landscape involving a myriad of protocols, standards, and work-arounds to integrate “legacy” devices, etc. We contend that users should not have to think about their world in terms of specific sensors, actuators, gateways, and protocols but rather in terms of room temperatures, the desire to increase the temperature in the living room, the concern that the plants in the garden are watered on time, etc. This creates a need to bridge this gap by creating a semantically meaningful layer of abstraction on top of the sensors and actuators that make up the “device and protocols oriented” Internet of Things, to create an Internet of Meaning. To this end, this chapter reports on the HESTIA framework, which combines: (1) An abstraction of the implementation details pertaining to, e.g., different protocols, standards, etc. (2) A domain-specific (conceptual) modeling framework in terms of which “things” can be captured in a way that is meaningful to the domain at hand (3) Based on this, a domain-specific language that is understandable by the user, enabling users to define control/behavioral rules in terms that are meaningful to them The presented HESTIA framework will be illustrated in terms of examples in the context of home and garden automation. Though such application contexts seem less challenging and complex than industrial Internet of Things applications, the variety of devices and protocols and distance between users and the technical details are often larger than in the case of industrial Internet of Things.

Keywords: GLSP, LSP, Modeling tool, Software modeling, UML, Web modeling
Astract: Web-based modeling tools provide unprecedented opportunities for the realization of modern, powerful, and usable diagram editors running in the cloud. The development of such tools, however, still poses significant challenges for developers. The graphical language server platform (GLSP) aims to reduce some of these challenges by providing the necessary frameworks to efficiently create web modeling tools. However, realizing modeling tools with GLSP remains challenging and not much support for interested tool developers is provided yet. This paper discusses these challenges and lessons learned after working with GLSP and realizing several GLSP-based modeling tools. We present experiences, concepts, and a reusable reference architecture to develop and operate GLSP-based web modeling tools. As a proof of concept, we report on the realization of a GLSP-based UML editor called bigUML. Through bigUML, we show that our procedure and the reference architecture we developed resulted in a scalable and flexible GLSP-based web modeling tool for the UML. The lessons learned, the procedural approach, the reference architecture, and the critical reflection on the challenges and opportunities of using GLSP provide valuable insights to the community and shall ease the decision of whether or not to use GLSP for future tool development projects. With this paper, we publicly release a reference implementation of our architecture.

Keywords: Enterprise Architecture, Architectural Coordination, Digital Twins for Urban Planning, Local Digital Twin
Astract: Digital Twins (DTs) carry the promise of improved decision-making about, as well as monitoring and understanding of, the twinned entity. This makes them an attractive instrument to support the, often complex and multi-faceted, decision-making processes germane to urban planning. DTs require considerable technological investments, as they tend to be data-hungry and computing-intensive. Business-wise, such investments are only meaningful if they really add value to the intended decision-making processes. However, most current DT development approaches primarily focus on the technological potential of DTs within the limited scope of isolated business scenarios, and rarely address trade-offs between costs and benefits towards the business case, let alone the broader implications for IT/IS portfolio management. These broader considerations are crucial in urban planning contexts, which typically involve a broad ecosystem of parties, complex decision-making challenges, and pre-existing technological landscapes. Drawing on the discipline of Enterprise Architecture Management (EAM), this paper argues that architectural coordination of DT development initiatives would enable more effective valorisation of DTs potential, and more effective management of DT-related technology within a broader technological landscape. To this end, the paper discusses the vision for and an initial sketch of a specialisation of EAM for DT development.

Keywords: CDS, Domain-specific language, Langium, LSP, Model-driven engineering, Modeling tool, SAP Core Data Services, Sprotty
Astract: This paper introduces bigER2CDS, a novel model-driven engineering approach and tool support for SAP Core Data Services (CDS). bigER2CDS addresses the need for a higher abstraction level in CDS development, enabling blended, i.e., textual and graphical modeling of CDS Views through a domain-specific modeling language. Based on web technologies and the Language Server Protocol (LSP), we realized a modeling tool for SAP CDS. Our tool supports the hybrid modeling of CDS and the import of existing SAP CDS view entities for analysis and development support. This model-driven approach aims to enable domain experts to develop CDS views, mitigating the need for extensive programming skills. We report on the development of the ER2CDS domain-specific language (DSL) and the implementation of the corresponding bigER2CDS modeling tool. Finally, bigER2CDS is evaluated in the form of a controlled experiment and a case study with domain experts and CDS developers. The results show a high usability score for our tool and a willingness by domain experts and CDS developers to use it. The tool can be freely downloaded from the VS Code marketplace: https://marketplace.visualstudio.com/items?itemName=BIGModelingTools.er2cds.

Keywords: Accessibility, Conceptual modeling, Disability, Modeling tools, Systematic literature review, Tool review
Astract: The reports on Disability by the World Health Organization show that the number of people with disabilities is increasing. Consequently, accessibility should play an essential role in information systems engineering research. While there is an increasingly rich set of available web accessibility guidelines, testing frameworks, and generally accessibility features in modern web-based software systems, software development frameworks, and Integrated Development Environments, this paper shows, based on a systematic review of the literature and current modeling tools, that accessibility is, so far, only scarcely focused in conceptual modeling research. With this paper, we assess the state of the art of accessibility in conceptual modeling, we identify current research gaps, and we delineate a vision toward more accessible conceptual modeling methods and tools. As a concrete step forward toward this vision, we present a generic concept of a keyboard-only modeling tool interaction that is implemented as a new module for the Graphical Language Server Platform (GLSP) framework. We show—using a currently developed UML modeling tool—how efficiently this module allows GLSP-based tool developers to introduce accessibility features into their modeling tools, thereby engaging physically disabled users in conceptual modeling.

Keywords: BERTopic, Data-driven approach, Dynamic Topic Modeling, EMMSAD, IS analysis and design
Astract: Modeling for information systems (IS) analysis and design offers broad insights into the advances and challenges of enterprise, business process, software, and conceptual modeling. In celebration of its 30th edition, this paper presents a data-driven retrospective analysis of studies published at the Exploring Modeling Methods for Systems Analysis and Development (EMMSAD) working conference from 2005 to 2024. EMMSAD has long been a key venue for research on Information Systems (IS) Modeling, covering areas such as conceptual modeling, enterprise modeling, and model-driven engineering, as well as the evaluation of modeling techniques and tools. Using machine learning, specifically Dynamic Topic Modeling (DTM) with BERTopic, this study identifies recurring topics, emerging trends, and shifts in research focus within the IS modeling community. The findings highlight key areas of alignment between IS modeling and the broader modeling landscape, providing insights into the field’s evolution and future research opportunities.

Keywords: design science, framework, maturity assessment, MBSE adoption
Astract: As engineering systems become increasingly complex, organizations must adopt strategic approaches to manage the interdependencies of their processes, tools, and teams. Model-Based Systems Engineering (MBSE) offers a promising solution, but transitioning from a traditional SE approach to MBSE is a complex endeavor that requires significant organizational change. This paper addresses the need for structured guidance in this process by proposing a maturity assessment framework that supports organizations in navigating this transition. The proposed framework is developed using a design science based approach and identifies key challenges, pitfalls, and best practices that are organized into several maturity levels of MBSE adoption. This structured, high-level approach provides organizations with the tools to understand their current maturity level, prioritize efforts, and avoid common missteps. The framework allows organizations to tailor the insights to their unique context, ensuring practical applicability. It emphasizes the importance of leadership, cultural readiness, technical tools, workforce development, and modeling practices for successful MBSE implementation.

Keywords: Conceptual Modeling Education, Learning Analytics Dashboards, Social Comparison
Astract: Conceptual modeling education benefits from technological support due to the complex nature of the learning processes required to master modeling skills. Along with existing modeling and prototyping tools, providing feedback to students using Learning Analytics Dashboards (LADs) can enhance their learning experience. To interpret LADs, students are provided with a frame of reference, often peer comparison, although its effectiveness is debated. This study presents two LADs used to provide feedback to students from diverse backgrounds enrolled in a conceptual modeling course: a default-LAD with mastery and progress reference frames, and an extended peer-LAD that also includes a performance reference frame. We examine students’ preferences for LAD visuals, the relationship between their study activity and performance, and the relationship between the use patterns of different LAD versions and student activity and performance. The results show that most of the relationships are significant only for the peer-enhanced LAD and are stronger for students with less modeling experience, underscoring the value of peer LADs for novice modelers.

Keywords: Digital Twin Engineering, Enterprise Architecture, Sustainable Real Estate Management
Astract: In the context of Real Estate Management, Digital Twins (DTs) can act as transformative tools for the integration of sustainability into construction practices by providing dynamic, data-driven virtual representations of physical assets. They enable stakeholders to optimise processes, reduce resource consumption, and align with sustainability objectives. However, effective implementation of DTs, in this context, remains limited by fragmented data ecosystems across different organisations, incomplete integration with regulatory frameworks, and insufficient consideration of sustainability goals. This is especially challenging, as access to high quality, and integrated, data is critical for DTs. Enterprise Architecture (EA) is generally used as an instrument to aid in managing and coordinating such challenges, as it provides a structured approach to addressing these challenges by aligning technical, organisational, and sustainability objectives. In line with this, we propose three primary research objectives: (1) assessing the current state of EA approaches for integrating DTs, (2) developing sustainability-oriented EA modelling concepts and design patterns, and (3) exploring the scalability of DTs from individual buildings to smart cities. Our aim is to position DTs as comprehensive decision-support tools for sustainability, enabling stakeholders to achieve better-informed decisions while addressing regulatory compliance, resource efficiency, and life cycle impacts.

Keywords: Conceptual Models, Domain Models, Modeling, Return on Modeling Efforts, Risk Assessment
Astract: Modelers and organizations often struggle to assess the benefits and drawbacks of modeling activities. This paper proposes addressing this challenge through a risk-oriented lens, leveraging the Common Ontology of ValuE and Risk (COVER) and the Reference Ontology for Security Engineering (ROSE). The proposal focuses on identifying assets at risk throughout the modeling process to clarify: when models mitigate risks and contribute to cost savings (models as risk deterrents), when models introduce risk to other assets (models as risk sources), or when they are vulnerable to risk events themselves (models as assets at risk), potentially generating additional costs. This perspective enables modelers and organizations to evaluate the benefits and costs of modeling practices, aligning investments with organizational goals, while helping researchers identify gaps for enhancing modeling languages, methods, and tools. The proposal is evaluated by analyzing case studies from the literature and interviews with nine professionals and researchers.